• DocumentCode
    2510088
  • Title

    Solving capacitated vehicle routing problem based on improved genetic algorithm

  • Author

    Jie-sheng, Wang ; Chang, Liu ; Ying, Zhang

  • Author_Institution
    Sch. of Electron. & Inf. Eng., Liaoning Univ. of Sci. & Technol., Anshan, China
  • fYear
    2011
  • fDate
    23-25 May 2011
  • Firstpage
    60
  • Lastpage
    64
  • Abstract
    Aiming at the capacitated vehicle routing problem (CVRP) in the matter stream delivery field, an improved genetic algorithm (GA) based on local mutation operator is adopted. Two layers chromosome coding scheme is designed which can improve initial solutions. This coding method can insure that the sub-routing is effective to satiety the vehicle capacitated constraints. These improved measures have important significance to depress procedural intricacy degree, advance convergence of algorithm velocity and algorithmic local search ability. The simulation experiment results show the improved genetic algorithm compared with BGA can achieve better optimization results and has better efficiency to solve CVRP.
  • Keywords
    genetic algorithms; logistics; road traffic; CVRP; advance convergence; algorithm velocity; algorithmic local search ability; capacitated vehicle routing problem; chromosome coding scheme; genetic algorithm; local mutation operator; matter stream delivery field; vehicle capacitated constraints; Biological cells; Encoding; Genetic algorithms; Genetics; Routing; Search problems; Vehicles; Capability Vehicle Routing Problem; Genetic Algorithm; Local Mutation; Two Layers Chromosome;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2011 Chinese
  • Conference_Location
    Mianyang
  • Print_ISBN
    978-1-4244-8737-0
  • Type

    conf

  • DOI
    10.1109/CCDC.2011.5968146
  • Filename
    5968146